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计算机工程 ›› 2012, Vol. 38 ›› Issue (01): 96-98,110. doi: 10.3969/j.issn.1000-3428.2012.01.027

• 网络与通信 • 上一篇    下一篇

基于K-means的无线家域网分簇算法

李晓卉,方康玲,何 坚   

  1. (武汉科技大学冶金自动化与检测技术教育部工程研究中心,武汉 430081)
  • 收稿日期:2011-07-21 出版日期:2012-01-05 发布日期:2012-01-05
  • 作者简介:李晓卉(1978-),女,副教授、博士,主研方向:无线传感器网络;方康玲,教授、博士生导师;何 坚,硕士研究生
  • 基金资助:
    国家自然科学基金青年基金资助项目(61105070);湖北省教育厅科学技术研究基金资助项目(B20111103)

Clustering Algorithm for Wireless Home Area Networks Based on K-means

LI Xiao-hui, FANG Kang-ling, HE Jian   

  1. (Engineering Research Center for Metallurgical Automation and Measurement Technology, Ministry of Education, Wuhan University of Science and Technology, Wuhan 430081, China)
  • Received:2011-07-21 Online:2012-01-05 Published:2012-01-05

摘要: 针对无线家域网的应用特点,提出一种基于K-means的无线家域网分簇算法。以LEACH协议中的最优分簇个数作为K-means聚类的输入参数,在家域网基站上实现集中式按需分簇,并利用Silhouette值判定最优的分簇及簇头。实验结果表明,在无线家域网仿真场景中,该算法能获得较好的分簇聚类效果。

关键词: 评价函数, 簇, 家域网, 无线传感器网络

Abstract: Aiming at the application characteristics of wireless Home Area Networks(HANs), this paper presents a K-means-based clustering algorithm for wireless HANs. The algorithm sets the optimal number of clusters in LEACH as the initial input parameters, and realizes the centralized and on-demand clustering on base station in home area networks, which makes use of Silhouette value to evaluate the optimal clustering. Experimental results show that this algorithm can get good clustering quality in wireless HANs simulation scene.

Key words: evaluation function, cluster, Home Area Networks(HANs), Wireless Sensor Network(WSN)

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